Decoupling government spending from carbon emissions: A spatio-temporal analysis of 283 Chinese cities

Abstract

A comprehensive evaluation of government spending efficiency and its connection to emissions reduction is vital for sustainable green economic progress. However, the precise nature of the decoupling relationship between carbon emissions and government spending at the city level remains uncertain. Here, using the panel data from 283 cities covering the period from 2007 to 2020, we employ diverse methodologies, such as Kernel density estimation and spatiotemporal autocorrelation analysis, to examine the spatiotemporal distribution of decoupling and identify key contributors through LMDI decomposition analysis. We find that initially, most cities demonstrated weak decoupling, but after 2010, a subset of cities achieved strong decoupling. The spatiotemporal distribution analysis highlights an expansion of inter-city differences in decoupling values and a reduction in the number of cities forming clusters after 2015. Furthermore, an increasing number of cities experienced positive emission intensity effects, while the positive effects of government spending on labor input consistently decreased. Initially, the positive effect of government spending on economic development declined but later showed a slight increase. The distribution of cities with a positive impact of government spending scale shifted from dispersed to concentrated in northern regions, resulting in a decrease in the number of cities with a positive impact.